Adopting sparsity in the field of fault detection was initially illustrated in Ref. [1]},
where basis pursuit denoising (BPD) [2]} was used to exploit sparse features in various domains to detect faults.
Some recent works consider other sparse representations for fault diagnosis
[3]}, [4]}, [5]}, [6]}.
The fault frequencies of potential bearing fault features
can be simply obtained using the geometry of the components in many cases
or directly obtained from the user operation manual.
Many works have considered the fault frequencies as priori information
[3]}, [8]}, [9]}, [10]}, [11]}.
